Russo decided that the results from Regression 1 was inconclusive for him to mak

Question

Russo decided that the results from Regression 1 was inconclusive for him to make decisions on the two MDPs (see description of the exam in the front) His boss, Stanley, came up and said to Russo, "whatever our ad copy or ad spending is, our competitor always spends $19!" Russo was suspicious of Stanley's assertion, so he ran a second regression with Competitor Ad Spending as the dependent variable. The results are shown below, and please explain: 1. What are the effects of the three independent variables (DumCopy, DumSeg, NopaneAd$) on Competitor's Ad Spending dollors? 2. Based on the regression results and your explanation in part 1 of this question, do you agree with Stanley or not? Explain why in details. Coefficients Standardized Coefficients Beta Unstandardized Coefficients Std. Error Sig Model (Constant) NopaneAds DumSeg DumCopy 9.713 851 917 9.083 2.726 425 1.920 1.920 293 .070 693 3.563 2.003 478 4.732 .002 .059 638 .000 a. Dependent Variable: CompAd$

Explanation / Answer

Here' the answer in detail. I've laid out the formulae and explanation for the answer. Please don't hesitate to give "a thumbs up" to the answer, in case you are satisfied with the answer.

1.

DumCopy: This variable is statistically significant since p-value is less than .05. Also, the coefficient of DumCopy is 9.083 which means that if DumCopy = 1, or the Adcopy increases by 1 unit, then the Competitor' Ad spending goes up by $9.083

NopaneAd: This variable is statistically not significant at alpha = .05. However, to interpret it, it means that per NoPanelAd $ incremental spending the Competitor'Ad spending increases by $.851

DumSeg: It also is an insigificant variable at .638. To interpret it , it means that per unit increase of this variable Competitor' Ad spending increases by $0.917.

But between these 3 variables, DumCopy with the highest standardized coefficient of .693 is the highest impacting variable. It is significant at alpha = .05 too.

2.

Since we can neglect the statistically not signifiant variables, we are left out with only 2 regressors: Constant and DumCopy, lets add up their coefficients to see if we get a value near or equal to $19

So, Comp. Ad. Spending ( predicted) = 9.713+9.083*1 = 18.796 or aaproximately $19.

Hence, Stanley is right, I would agree with Stanley

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